FinOps as Code: Exploring Active Resource Data

The blog post explores the use of FinOps as Code to analyze active cost-generating resources within a cloud environment using the Vantage API. It provides a tutorial that guides users through utilizing a Jupyter Notebook and Python libraries such as requests, pandas, matplotlib, and seaborn to visualize and gain insights into their cloud spending. By examining active resources, users can identify where their organization incurs the most significant costs, helping them make informed decisions on resource configuration and usage patterns. The tutorial covers steps for retrieving data from the Vantage API, handling pagination and rate limits, and creating data visualizations like bar charts and heatmaps to highlight top cost-contributing resources by type, region, and provider. These visualizations assist in identifying areas for potential cost optimization, such as investigating high-cost regions or resource types and considering cost-reduction strategies like shifting workloads to more cost-effective locations. The post emphasizes the importance of monitoring cloud resources to prevent unexpected expenses and suggests further analysis for deeper insights into resource usage and costs.